Welcome to SciNance
Quantitative analysts ("Quants") use a number of scientific numerical methods to understand and predict the stock market. Quants apply these methods to investment management, risk management, derivatives pricing, statistical arbitrage, algorithmic trading, and electronic market making. Quants are the scientists of Wall Street, and are responsible for structuring the financial instruments that control world economics. Quantitative analysts typically come from theoretical physics/chemistry, engineering, or mathematics backgrounds rather than economics-related fields. In fact, many hedge funds prefer Ph.D. scientists with no background in economics, since such a background can introduce unwanted market bias into the models. Quantitative analysis is a major source of employment for people with quantitative science Ph.Ds. Typically, a quantitative analyst will also need extensive skills in object oriented computer programming, most commonly C++ and/or Java.
Many methods used in scientific computing are applied to finance. Everything from Monte Carlo simulation for the pricing of options, to machine learning/artificial intelligence for market prediction. Theories stemming from quantum mechanics and relativity are also employed in real-world financial applications.
Some key areas quants are involved in include the folllowing:
Front office quantitative analysis
Quantitative investment management
Library quantitative analysis
Algorithmic trading quantitative analysis
Risk management
Innovation
Model validation
Quantitative development
More focused areas include:
Trading strategy development
Portfolio optimization
Derivatives pricing and hedging: involves a lot of highly efficient (usually object-oriented) software development, advanced numerical techniques, and stochastic calculus
Risk management: involves a lot of time series analysis, calibration, and backtesting
Credit analysis
Welcome to SciNance, the blog dedicated to educating both scientists and economists about the world of financial engineering.
